scholarly journals Self-regulated learning and critical reflection in an e-learning on patient safety for third-year medical students

2018 ◽  
Vol 9 ◽  
pp. 189-194 ◽  
Author(s):  
Rainer Gaupp ◽  
Götz Fabry ◽  
Mirjam Körner
Keyword(s):  
Patient Safety ◽  
Medical Students ◽  
Critical Reflection ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
E Learning

scholarly journals Relationships between medical students’ co-regulatory network characteristics and self-regulated learning: a social network study

2021 ◽  
Author(s):  
Derk Bransen ◽  
Marjan J. B. Govaerts ◽  
Dominique M. A. Sluijsmans ◽  
Jeroen Donkers ◽  
Piet G. C. Van den Bossche ◽  
...  
Keyword(s):  
Social Network ◽  
Medical Students ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Learning Opportunities ◽  
Network Size ◽  
Tie Strength ◽  
Network Characteristics ◽  
Self Regulated Learning ◽  
Regulated Learning

Abstract Introduction Recent conceptualizations of self-regulated learning acknowledge the importance of co-regulation, i.e., students’ interactions with others in their networks to support self-regulation. Using a social network approach, the aim of this study is to explore relationships between characteristics of medical students’ co-regulatory networks, perceived learning opportunities, and self-regulated learning. Methods The authors surveyed 403 undergraduate medical students during their clinical clerkships (response rate 65.5%). Using multiple regression analysis, structural equation modelling techniques, and analysis of variance, the authors explored relationships between co-regulatory network characteristics (network size, network diversity, and interaction frequency), students’ perceptions of learning opportunities in the workplace setting, and self-reported self-regulated learning. Results Across all clerkships, data showed positive relationships between tie strength and self-regulated learning (β = 0.095, p < 0.05) and between network size and tie strength (β = 0.530, p < 0.001), and a negative relationship between network diversity and tie strength (β = −0.474, p < 0.001). Students’ perceptions of learning opportunities showed positive relationships with both self-regulated learning (β = 0.295, p < 0.001) and co-regulatory network size (β = 0.134, p < 0.01). Characteristics of clerkship contexts influenced both co-regulatory network characteristics (size and tie strength) and relationships between network characteristics, self-regulated learning, and students’ perceptions of learning opportunities. Discussion The present study reinforces the importance of co-regulatory networks for medical students’ self-regulated learning during clinical clerkships. Findings imply that supporting development of strong networks aimed at frequent co-regulatory interactions may enhance medical students’ self-regulated learning in challenging clinical learning environments. Social network approaches offer promising ways of further understanding and conceptualising self- and co-regulated learning in clinical workplaces.

scholarly journals Factors affecting self-regulated learning in medical students: a qualitative study

2015 ◽  
Vol 20 (1) ◽  
pp. 28694 ◽  
Author(s):  
Zahra Jouhari ◽  
Fariba Haghani ◽  
Tahereh Changiz
Keyword(s):  
Medical Students ◽  
Qualitative Study ◽  
Factors Affecting ◽  
Self Regulated Learning ◽  
Regulated Learning

A Conceptual Educational Data Mining Model for Supporting Self-Regulated Learning in Online Learning Environments

2021 ◽  
pp. 278-292
Author(s):  
Eric Araka ◽  
Robert Oboko ◽  
Elizaphan Maina ◽  
Rhoda K. Gitonga
Keyword(s):  
Data Mining ◽  
Online Learning ◽  
Learning Environments ◽  
Domain Knowledge ◽  
Educational Data Mining ◽  
Online Learning Environments ◽  
Student Activities ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
E Learning

Self-regulated learning is attracting tremendous researches from various communities such as information communication technology. Recent studies have greatly contributed to the domain knowledge that the use self-regulatory skills enhance academic performance. Despite these developments in SRL, our understanding on the tools and instruments to measure SRL in online learning environments is limited as the use of traditional tools developed for face-to-face classroom settings are still used to measure SRL on e-learning systems. Modern learning management systems (LMS) allow storage of datasets on student activities. Subsequently, it is now possible to use Educational Data Mining to extract learner patterns which can be used to support SRL. This chapter discusses the current tools for measuring and promoting SRL on e-learning platforms and a conceptual model grounded on educational data mining for implementation as a solution to promoting SRL strategies.

The Effects of Web-Enabled Self-Regulated Learning and Problem-Based Learning with Initiation on Students' Computing Skills

2011 ◽  
pp. 1614-1627
Author(s):  
Pei-Di Shen
Keyword(s):  
Online Teaching ◽  
Teaching Method ◽  
Problem Based Learning ◽  
Work Force ◽  
Vocational Schools ◽  
Web Based ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Computing Skills ◽  
E Learning

Vocational degree earners represent a major portion of the work force in Taiwan. However, the reality of computing education in Taiwan’s vocational schools is that it’s not so practically oriented, revealing much room for improvement. In this context, we conducted a quasi-experiment to examine the effects of applying web-based self-regulated learning, web-based problem-based learning with initiation, and their combination to enhance students’ computing skills. Four classes in successive years, with a total of 177 third-year students, were divided into 2 (SRL vs. non-SRL) × 2 (PBL with initiation vs. PBL without initiation) experimental groups. Results were generally positive. Results revealed that the effects of webenabled SRL, web-enabled PBL with initiation, and their combinations on students’ computing skills have significant differences. We hope that the online teaching method applied in this study is also useful for those teachers engaged in e-learning, specifically, in vocational schools.

scholarly journals Flipped Classroom for Improving Self-Regulated Learning of Pre-Service Teachers

2020 ◽  
Vol 14 (09) ◽  
pp. 110 ◽  
Author(s):  
Cecep Kustandi ◽  
Hirmana Wargahadibrata ◽  
Dini Nur Fadhillah ◽  
Suprayekti Suprayekti ◽  
Kunto Imbar Nursetyo
Keyword(s):  
Learning Outcomes ◽  
Mixed Method ◽  
Flipped Classroom ◽  
Self Regulated Learning ◽  
Self Confidence ◽  
Regulated Learning ◽  
Study Programs ◽  
E Learning ◽  
Faculty Of Education ◽  
Education Science

<p class="0abstract">This study aims to describe the use of the flipped classroom for improving the self-regulated learning of pre-service teachers. This explanatory mixed-method collected the information related to the characteristics of students who take Theory Learning courses through e-learning. This research collaborated with students of 2018 which included 30 students and 7 lecturers of Theory Learning courses from 7 study programs at the Faculty of Education Science, Universitas Negeri Jakarta. The results show by a one-tailed test at a significant level 0,05 with n-1 = 29 is 2,045, so tcount (5,843) &gt; ttable (2,045), means an increase after the use of flipped classroom learning outcomes in Theory Learning courses. And also improving self-regulated students. It can be concluded that in general the learning independence of the students of the Faculty of Education Science of Universitas Negeri Jakarta in the indicators has self-confidence categorized as positive<strong>.</strong></p>

scholarly journals Nomograms Predicting Self-Regulated Learning Levels in Chinese Undergraduate Medical Students

2020 ◽  
Vol 10 ◽  
Author(s):  
Jun Yang ◽  
Guoyang Zhang ◽  
Runzhi Huang ◽  
Penghui Yan ◽  
Peng Hu ◽  
...  
Keyword(s):  
Medical Students ◽  
Undergraduate Medical Students ◽  
Self Regulated Learning ◽  
Regulated Learning

scholarly journals Long-term effects of an e-learning course on patient safety: A controlled longitudinal study with medical students

PLoS ONE ◽  
2019 ◽  
Vol 14 (1) ◽  
pp. e0210947 ◽  
Author(s):  
Rainer Gaupp ◽  
Julia Dinius ◽  
Ivana Drazic ◽  
Mirjam Körner
Keyword(s):  
Patient Safety ◽  
Longitudinal Study ◽  
Medical Students ◽  
Long Term Effects ◽  
E Learning
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